Impact of agricultural chemicals on the environment and human health in Asia: Are there solutions?

Modern commercial agricultural practices in Asia during the last three to four decades involving chemicals (fertilisers and pesticides) have been associated with large increases in food production never witnessed before, especially under the Green Revolution technology in South Asia. This also involves large-scale increases in commercial vegetable crops. However, the high reliance on chemical inputs to bring about these increases in food production is not without problems. A visible, parallel correlation between higher productivity, high artificial input use and environmental degradation and human ill-health is evident in many countries where commercial agriculture is widespread. In this chapter, we focus on the impact of chemical inputs, in particular the impact of pesticides on the environment and on human health in South Asia with special reference to Sri Lanka...

Bringing the farmer perspective to agricultural robots

The research reported in this paper explores autonomous technologies for agricultural farming application and is focused on the development of multiple-cooperative agricultural robots (AgBots). These are highly autonomous, small, lightweight, and unmanned machines that operate cooperatively (as opposed to a traditional single heavy machine) and are suited to work on broadacre land (large-scale crop operations on land parcels greater than 4,000m2). Since this is a new, and potentially disruptive technology, little is yet known about farmer attitudes towards robots, how robots might be incorporated into current farming practice, and how best to marry the capability of the robot with the work of the farmer. This paper reports preliminary insights (with a focus on farmer-robot control) gathered from field visits and contextual interviews with farmers, and contributes knowledge that will enable further work toward the design and application of agricultural robotics.

Design of a lightweight, modular robotic vehicle for the sustainable intensification of broadacre agriculture

This thesis presents the design process and the prototyping of a lightweight, modular robotic vehicle for the sustainable intensification of broadacre agriculture. Achieved by the joint operation of multiple autonomous vehicles to improve energy consumption, reduce labour, and increase efficiency in the application of inputs for the management of crops. The Small Robotic Farm Vehicle (SRFV) is a lightweight and energy efficient robotic vehicle with a configurable, modular design. It is capable of undertaking a range of agricultural tasks, including fertilising and weed management through mechanical intervention and precision spraying, whilst being more than an order of magnitude lower in weight than existing broadacre agricultural equipment.

Export of radioactive cesium from agricultural fields under simulated rainfall in Fukushima

In this study, we investigated the impact of rainfall on runoff, soil erosion and consequently on the discharge of radioactive cesium in agricultural fields in Fukushima prefecture using a rainfall simulator. Simulated heavy rainfalls (50 mm h-1) generated significant runoff and soil erosion. The average concentration of radioactive cesium (the sum of 134Cs and 137Cs) in the runoff sediments was [similar]3500 Bq kg-1 dry soil, more than double the concentrations measured in the field soils which should be considered in studies using the 137Cs loss to estimate long-term soil erosion. However, the estimated mass of cesium discharged through one runoff event was less than 2% of the cesium inventory in the field. This suggested that cesium discharge via soil erosion is not a significant factor in reducing the radioactivity of contaminated soils in Fukushima prefecture. However, the eroded sediment carrying radioactive cesium will deposit into the river systems and potentially pose a radioactivity risk for aquatic living organisms.

‘Lemon Laws’: an inquiry into consumer protections and remedies for buyers of new motor vehicles

1. Under the Terms of Reference for the Committee’s Inquiry, ‘lemons’ are defined as ‘new motor vehicles with numerous, severe defects that re-occur despite multiple repair attempts or where defects have caused a new motor vehicle to be out of service for a prolonged period of time’. Consumers are currently protected in relation to lemon purchases by the Australian Consumer Law (ACL) located in Schedule 2 of the Competition and Consumer Act 2010 (Cth) (CCA). The ACL applies as a law of Queensland pursuant to the Fair Trading Act 1989 (Qld). The voluntary recall and consumer guarantees law took effect on 1 January 2011. 2. In 2006, the Government of Victoria made a commitment to introduce a lemon law into the provisions of the then Fair Trading Act 1999 (Vic). The public consultation process on the proposal to introduce a lemon law for motor vehicle purchases in Victoria was conducted by Ms Janice Munt MP, with the assistance of Consumer Affairs Victoria (CAV). CAV released an Issues Paper to canvas with industry and the community options for the development and introduction of a motor vehicle lemon law.(Consumer Affairs Victoria, Introducing Victorian motor vehicle lemon laws, Issues Paper, (September, 2007). 3. A CAV report prepared by Janice Munt MP was released in July, 2008 (Consumer Affairs Victoria, Motor Cars: A report on the motor vehicle lemon law consultations (July 2008) (Victorian Lemon Law Report). However, the Victorian proposal was overtaken by events leading to the adoption of a uniform consumer protection law in all Australian jurisdictions, the ACL. 4. The structure of this submission is to consider first the three different bases upon which consumers can obtain relief for economic loss arising from defects in motor vehicles. The second part of the submission considers the difficulties encountered by consumers in litigating motor vehicle disputes in the courts and tribunals. The third part of the submission examines the approach taken in other jurisdictions to resolving motor vehicle disputes. The final part of the submission considers a number of possible reforms that could be made to the existing law and its enforcement to reduce consumer detriment arising from the purchase of ‘lemon’ motor vehicles. 5. There are three principal bases upon which a consumer can obtain redress for defects in new motor vehicles under the ACL. The first is where the manufacturer admits liability and initiates the voluntary recall procedure provided for in s 128 of the ACL. Under this basis the manufacturer generally repairs or replaces the part subject to the recall free of charge. The second basis is where the manufacturer or dealer denies liability and the consumer is initiates proceedings in the court or tribunal seeking a statutory remedy under the ACL, the nature of which will depend on whether the failure to comply with the consumer guarantee was major or not. The third basis upon which a consumer can obtain redress is pursuant to public enforcement by the ACCC. Each basis will be considered in this part. What all three bases have in common is the need to conduct an investigation to identify the nature of the defect and how it arose.

Design and flight testing of a bio-inspired plume tracking algorithm for unmanned serial vehicles

There is an increased interest on the use of UAVs for environmental research such as tracking bush fires, volcanic eruptions, chemical accidents or pollution sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A method for generating sparse plumes in a virtual environment was also developed. Results indicated the ability of the algorithms to track plumes in 2D and 3D. The system has been tested with hardware in the loop (HIL) simulations and in flight using a CO2 gas sensor mounted to a multi-rotor UAV. The UAV is controlled by the plume tracking algorithm running on the ground control station (GCS).

Crude oil and agricultural futures: An analysis of correlation dynamics

Correlations between oil and agricultural commodities have varied over previous decades, impacted by renewable fuels policy and turbulent economic conditions. We estimate smooth transition conditional correlation models for 12 agricultural commodities and WTI crude oil. While a structural change in correlations occurred concurrently with the introduction of biofuel policy, oil and food price levels are also key influences. High correlation between biofuel feedstocks and oil is more likely to occur when food and oil price levels are high. Correlation with oil returns is strong for biofuel feedstocks, unlike with other agricultural futures, suggesting limited contagion from energy to food markets.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.